Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review
Magnetic resonance imaging (MRI) stands as a vital medical imaging technique, renowned
for its ability to offer high-resolution images of the human body with remarkable soft-tissue …
for its ability to offer high-resolution images of the human body with remarkable soft-tissue …
Magnetic resonance fingerprinting: a review of clinical applications
Magnetic resonance fingerprinting (MRF) is an approach to quantitative magnetic resonance
imaging that allows for efficient simultaneous measurements of multiple tissue properties …
imaging that allows for efficient simultaneous measurements of multiple tissue properties …
Magnetic resonance fingerprinting using recurrent neural networks
Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic
resonance imaging that allows simultaneous measurement of multiple tissue properties in a …
resonance imaging that allows simultaneous measurement of multiple tissue properties in a …
Only‐train‐once MR fingerprinting for B0 and B1 inhomogeneity correction in quantitative magnetization‐transfer contrast
Purpose To develop a fast, deep‐learning approach for quantitative magnetization‐transfer
contrast (MTC)–MR fingerprinting (MRF) that simultaneously estimates multiple tissue …
contrast (MTC)–MR fingerprinting (MRF) that simultaneously estimates multiple tissue …
A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions
This work presents a deep learning approach for rapid and accurate muscle water T2 with
subject-specific fat T2 calibration using multi-spin-echo acquisitions. This method addresses …
subject-specific fat T2 calibration using multi-spin-echo acquisitions. This method addresses …
Deep learning‐assisted preclinical MR fingerprinting for sub‐millimeter T1 and T2 mapping of entire macaque brain
Abstract Purpose Preclinical MR fingerprinting (MRF) suffers from long acquisition time for
organ‐level coverage due to demanding image resolution and limited undersampling …
organ‐level coverage due to demanding image resolution and limited undersampling …
Channel attention networks for robust MR fingerprint matching
Objective: Magnetic Resonance Fingerprinting (MRF) enables simultaneous mapping of
multiple tissue parameters such as T1 and T2 relaxation times. The working principle of MRF …
multiple tissue parameters such as T1 and T2 relaxation times. The working principle of MRF …
Bayesian inverse regression for vascular magnetic resonance fingerprinting
Standard parameter estimation from vascular magnetic resonance fingerprinting (MRF) data
is based on matching the MRF signals to their best counterparts in a grid of coupled …
is based on matching the MRF signals to their best counterparts in a grid of coupled …
TSP-GNN: a novel neuropsychiatric disorder classification framework based on task-specific prior knowledge and graph neural network
J Lang, LZ Yang, H Li - Frontiers in Neuroscience, 2023 - frontiersin.org
Neuropsychiatric disorder (ND) is often accompanied by abnormal functional connectivity
(FC) patterns in specific task contexts. The distinctive task-specific FC patterns can provide …
(FC) patterns in specific task contexts. The distinctive task-specific FC patterns can provide …
[HTML][HTML] Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain
Introduction This study explores the potential of Magnetic Resonance Fingerprinting (MRF)
with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous …
with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous …